Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n to (exclusive):

File format (GeoTiff, NetCDF):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2024-01-04 10:20:15	ga_s2am_ard_3-2-1_54LWN_2024-01-04_final
2024-01-04 10:20:24	ga_s2am_ard_3-2-1_54LXM_2024-01-04_final
2024-01-04 10:20:32	ga_s2am_ard_3-2-1_54LZL_2024-01-04_final
2024-01-04 10:21:04	ga_s2am_ard_3-2-1_54LYJ_2024-01-04_final
2024-01-04 10:21:19	ga_s2am_ard_3-2-1_54LYH_2024-01-04_final
2024-01-04 10:21:29	ga_s2am_ard_3-2-1_54LVH_2024-01-04_final
2024-01-04 10:21:34	ga_s2am_ard_3-2-1_54KYG_2024-01-04_final
2024-01-04 10:21:40	ga_s2am_ard_3-2-1_54KWG_2024-01-04_final
2024-01-04 10:22:06	ga_s2am_ard_3-2-1_54KXE_2024-01-04_final
2024-01-04 10:22:10	ga_s2am_ard_3-2-1_54KYD_2024-01-04_final
2024-01-04 10:22:13	ga_s2am_ard_3-2-1_54KVE_2024-01-04_final
2024-01-04 10:22:20	ga_s2am_ard_3-2-1_54KXD_2024-01-04_final
2024-01-04 10:22:31	ga_s2am_ard_3-2-1_54KUD_2024-01-04_final
2024-01-04 10:23:07	ga_s2am_ard_3-2-1_54KWA_2024-01-04_final
2024-01-04 10:23:11	ga_s2am_ard_3-2-1_54KVA_2024-01-04_final
2024-01-04 10:23:14	ga_s2am_ard_3-2-1_54KUA_2024-01-04_final
2024-01-04 10:23:26	ga_s2am_ard_3-2-1_54KVV_2024-01-04_final
2024-01-04 10:23:29	ga_s2am_ard_3-2-1_54KUV_2024-01-04_final
2024-01-04 10:23:36	ga_s2am_ard_3-2-1_53KRQ_2024-01-04_final
2024-01-04 10:24:12	ga_s2am_ard_3-2-1_54JUS_2024-01-04_final
2024-01-04 10:24:38	ga_s2am_ard_3-2-1_54JVQ_2024-01-04_final
2024-01-04 10:24:53	ga_s2am_ard_3-2-1_54JVP_2024-01-04_final
2024-01-04 10:25:17	ga_s2am_ard_3-2-1_53JQH_2024-01-04_final
2024-01-04 10:25:25	ga_s2am_ard_3-2-1_54JUM_2024-01-04_final
2024-01-04 10:25:32	ga_s2am_ard_3-2-1_54JVL_2024-01-04_final
2024-01-04 10:25:49	ga_s2am_ard_3-2-1_53JPF_2024-01-04_final
2024-01-04 10:26:04	ga_s2am_ard_3-2-1_53HPE_2024-01-04_final
2024-01-04 10:26:14	ga_s2am_ard_3-2-1_53HQD_2024-01-04_final
2024-01-04 10:26:30	ga_s2am_ard_3-2-1_53HNC_2024-01-04_final
2024-01-04 10:26:31	ga_s2am_ard_3-2-1_54HTH_2024-01-04_final
2024-01-04 10:26:43	ga_s2am_ard_3-2-1_53HQB_2024-01-04_final
2024-01-04 10:26:47	ga_s2am_ard_3-2-1_54HUF_2024-01-04_final
2024-01-04 10:26:50	ga_s2am_ard_3-2-1_53HNB_2024-01-04_final
2024-01-04 10:27:01	ga_s2am_ard_3-2-1_53HPA_2024-01-04_final
2024-01-04 10:27:11	ga_s2am_ard_3-2-1_53HPV_2024-01-04_final
2024-01-04 12:03:41	ga_s2am_ard_3-2-1_50KNA_2024-01-04_final
2024-01-04 12:03:41	ga_s2am_ard_3-2-1_49KHS_2024-01-04_final
2024-01-04 12:03:49	ga_s2am_ard_3-2-1_50KMA_2024-01-04_final
2024-01-04 12:03:55	ga_s2am_ard_3-2-1_50KKA_2024-01-04_final
2024-01-04 12:03:56	ga_s2am_ard_3-2-1_49KHR_2024-01-04_final
2024-01-04 12:04:07	ga_s2am_ard_3-2-1_50KLV_2024-01-04_final
2024-01-04 12:04:10	ga_s2am_ard_3-2-1_50KKV_2024-01-04_final
2024-01-04 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2024-01-04_final
2024-01-04 12:04:18	ga_s2am_ard_3-2-1_50KMU_2024-01-04_final
2024-01-04 12:04:21	ga_s2am_ard_3-2-1_50KLU_2024-01-04_final
2024-01-04 12:04:28	ga_s2am_ard_3-2-1_49KGP_2024-01-04_final
2024-01-04 12:04:39	ga_s2am_ard_3-2-1_50JKT_2024-01-04_final
2024-01-04 12:04:45	ga_s2am_ard_3-2-1_50JMS_2024-01-04_final
2024-01-04 12:04:50	ga_s2am_ard_3-2-1_50JLS_2024-01-04_final
2024-01-04 12:04:54	ga_s2am_ard_3-2-1_50JKS_2024-01-04_final
2024-01-04 12:04:57	ga_s2am_ard_3-2-1_49JGM_2024-01-04_final
2024-01-04 12:05:08	ga_s2am_ard_3-2-1_50JKR_2024-01-04_final
2024-01-04 12:05:11	ga_s2am_ard_3-2-1_49JGL_2024-01-04_final
2024-01-04 12:05:34	ga_s2am_ard_3-2-1_50JLP_2024-01-04_final
2024-01-04 12:05:55	ga_s2am_ard_3-2-1_49JGH_2024-01-04_final
2024-01-04 12:06:06	ga_s2am_ard_3-2-1_50JKM_2024-01-04_final
2024-01-04 12:06:11	ga_s2am_ard_3-2-1_50JLL_2024-01-04_final
2024-01-05 09:54:24	ga_s2am_ard_3-2-1_55JFK_2024-01-05_final
2024-01-05 09:56:54	ga_s2am_ard_3-2-1_54HXF_2024-01-05_final
2024-01-05 09:57:42	ga_s2am_ard_3-2-1_54HWC_2024-01-05_final
2024-01-05 09:58:02	ga_s2am_ard_3-2-1_54GYA_2024-01-05_final
2024-01-05 11:31:32	ga_s2am_ard_3-2-1_51LZD_2024-01-05_final
2024-01-05 11:32:16	ga_s2am_ard_3-2-1_51KVB_2024-01-05_final
2024-01-05 11:33:30	ga_s2am_ard_3-2-1_51KUS_2024-01-05_final
2024-01-05 11:34:45	ga_s2am_ard_3-2-1_50JRS_2024-01-05_final
2024-01-05 11:35:04	ga_s2am_ard_3-2-1_51JWK_2024-01-05_final
2024-01-05 11:35:37	ga_s2am_ard_3-2-1_51JUH_2024-01-05_final
2024-01-06 09:25:03	ga_s2am_ard_3-2-1_56JNM_2024-01-05_final
2024-01-06 09:25:26	ga_s2am_ard_3-2-1_56JLL_2024-01-05_final
2024-01-14 12:00:27	ga_s2am_ard_3-2-1_50LQP_2024-01-14_nrt
2024-01-14 12:00:33	ga_s2am_ard_3-2-1_50LNP_2024-01-14_nrt
2024-01-14 12:01:03	ga_s2am_ard_3-2-1_50LNM_2024-01-14_nrt
2024-01-14 12:01:06	ga_s2am_ard_3-2-1_50LMM_2024-01-14_nrt
2024-01-14 12:01:17	ga_s2am_ard_3-2-1_50LNL_2024-01-14_nrt
2024-01-14 12:01:20	ga_s2am_ard_3-2-1_50LML_2024-01-14_nrt
2024-01-14 12:01:30	ga_s2am_ard_3-2-1_50LMK_2024-01-14_nrt
2024-01-14 12:02:52	ga_s2am_ard_3-2-1_50KLE_2024-01-14_nrt
2024-01-14 12:03:11	ga_s2am_ard_3-2-1_49KHU_2024-01-14_nrt
2024-01-14 12:03:23	ga_s2am_ard_3-2-1_49KHT_2024-01-14_nrt
2024-01-14 12:06:16	ga_s2am_ard_3-2-1_49JGF_2024-01-14_nrt
2024-01-15 09:49:37	ga_s2am_ard_3-2-1_56LKP_2024-01-15_nrt
2024-01-15 09:49:51	ga_s2am_ard_3-2-1_56LKN_2024-01-15_nrt
2024-01-15 09:49:58	ga_s2am_ard_3-2-1_56LKM_2024-01-15_nrt
2024-01-15 09:50:52	ga_s2am_ard_3-2-1_56LLJ_2024-01-15_nrt
2024-01-15 09:50:54	ga_s2am_ard_3-2-1_56LKJ_2024-01-15_nrt
2024-01-15 09:50:57	ga_s2am_ard_3-2-1_56LLH_2024-01-15_nrt
2024-01-15 09:50:58	ga_s2am_ard_3-2-1_55LFD_2024-01-15_nrt
2024-01-15 09:57:51	ga_s2am_ard_3-2-1_54HWB_2024-01-15_nrt
2024-01-15 09:58:02	ga_s2am_ard_3-2-1_54GXA_2024-01-15_nrt
2024-01-15 09:58:06	ga_s2am_ard_3-2-1_54GWA_2024-01-15_nrt
2024-01-15 09:58:16	ga_s2am_ard_3-2-1_54GXV_2024-01-15_nrt
2024-01-15 09:58:19	ga_s2am_ard_3-2-1_54GWV_2024-01-15_nrt
2024-01-15 09:58:24	ga_s2am_ard_3-2-1_54GXU_2024-01-15_nrt
2024-01-15 11:30:07	ga_s2am_ard_3-2-1_52LCP_2024-01-15_nrt
2024-01-15 11:30:14	ga_s2am_ard_3-2-1_52LBP_2024-01-15_nrt
2024-01-15 11:30:19	ga_s2am_ard_3-2-1_51LYJ_2024-01-15_nrt
2024-01-15 11:30:26	ga_s2am_ard_3-2-1_52LBN_2024-01-15_nrt
2024-01-15 11:30:29	ga_s2am_ard_3-2-1_51LYH_2024-01-15_nrt
2024-01-15 11:30:32	ga_s2am_ard_3-2-1_52LBN_2024-01-15_nrt
2024-01-15 11:37:21	ga_s2am_ard_3-2-1_51HTA_2024-01-15_nrt

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years